Dataset Information

PICU Length of Stay: Factors Associated With Bed Utilization and Development of a Benchmarking Model.

ABSTRACT: OBJECTIVES:ICU length of stay is an important measure of resource use and economic performance. Our primary aims were to characterize the utilization of PICU beds and to develop a new model for PICU length of stay. DESIGN:Prospective cohort. The main outcomes were factors associated with PICU length of stay and the performance of a regression model for length of stay. SETTING:Eight PICUs. PATIENTS:Randomly selected patients (newborn to 18 yr) from eight PICUs were enrolled from December 4, 2011, to April 7, 2013. Data consisted of descriptive, diagnostic, physiologic, and therapeutic information. INTERVENTIONS:None. MEASUREMENTS AND MAIN RESULTS:The mean length of stay for was 5.0 days (SD, 11.1), with a median of 2.0 days. The 50.6% of patients with length of stay less than 2 days consumed only 11.1% of the days of care, whereas the 19.6% of patients with length of stay 4.9-19 days and the 4.6% with length of stay greater than or equal to 19 days consumed 35.7% and 37.6% of the days of care, respectively. Longer length of stay was observed in younger children, those with cardiorespiratory disease, postintervention cardiac patients, and those who were sicker assessed by Pediatric Risk of Mortality scores receiving more intensive therapies. Patients in the cardiac ICU stayed longer than those in the medical ICU. The length of stay model using descriptive, diagnostic, severity, and therapeutic factors performed well (patient-level R-squared of 0.42 and institution-level R-squared of 0.76). Standardized (observed divided by expected) length of stay ratios at the individual sites ranged from 0.87 to 1.09. CONCLUSIONS:PICU bed utilization was dominated by a minority of patients. The 5% of patients staying the longest used almost 40% of the bed days. The multivariate length of stay model used descriptive, diagnostic, therapeutic, and severity factors and has potential applicability for internal and external benchmarking.

SUBMITTER: Pollack MM

PROVIDER: S-EPMC5834365 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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PICU Length of Stay: Factors Associated With Bed Utilization and Development of a Benchmarking Model.

Pollack Murray M MM Holubkov Richard R Reeder Ron R Dean J Michael JM Meert Kathleen L KL Berg Robert A RA Newth Christopher J L CJL Berger John T JT Harrison Rick E RE Carcillo Joseph J Dalton Heidi H Wessel David L DL Jenkins Tammara L TL Tamburro Robert R

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies 20180301 3

<h4>Objectives</h4>ICU length of stay is an important measure of resource use and economic performance. Our primary aims were to characterize the utilization of PICU beds and to develop a new model for PICU length of stay.<h4>Design</h4>Prospective cohort. The main outcomes were factors associated with PICU length of stay and the performance of a regression model for length of stay.<h4>Setting</h4>Eight PICUs.<h4>Patients</h4>Randomly selected patients (newborn to 18 yr) from eight PICUs were en ...[more]

PMID: 29239978

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Project description:BackgroundPredicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient's "bed pathway" - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy.MethodsWe obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020.ResultsIn both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: "Ward, CC, Ward", "Ward, CC", "CC" and "CC, Ward". Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities.ConclusionsWe identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19.Trial registrationThe ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.

Project description:AimAppraise the clinical features and influencing factors of the hospitalization times and length of stay in bipolar disorder (BD) patients.MethodsThis is a multicenter, observational, cohort study of patients diagnosed of type I or type II bipolar disorder. Five hundred twenty outpatients in seven hospitals from six cities in China were recruited from February 2013 to June 2014 and followed up using a continuous sampling pattern. The research included a retrospective period of 12 months and the prospective period of 9 months. The demographic and clinical features of the patients were collected. The influencing factors that could affect the length of stay (number of days spent in the hospital in the prospective period) were analyzed by poisson's regression and the hospitalization times (times of hospitalization in the prospective and retrospective period) was analyzed by general linear model. The selected variables included gender, age, years of education, occupational status, residence status, family history of mental disease, comorbid substance abuse, comorbid anxiety disorder, times of suicide (total suicide times that occurred in the retrospective and prospective period), polarity of the first mood episode, and BD type(I/II).ResultsPoisson's regression analysis showed that suicide times [Incidence Rate Ratio (IRR) = 1.20, p < 0.001], use of antipsychotic (IRR = 0.62, p = 0.011), and use of antidepressant (IRR = 0.56, p < 0.001) were correlated to more hospitalization times. Linear regression analysis showed that BD type II (β = 0.28, p = 0.005) and unemployment (β = 0.16, p = 0.039) which might mean longer duration of depression and poor function were correlated to longer length of stay. However, patients who experienced more suicide times (β = -0.21, p = 0.007) tended to have a shorter length of stay.ConclusionOverall, better management of the depressive episode and functional rehabilitation may help to reduce the length of stay. BD patients with more hospitalization times were characterized by higher risk of suicide and complex polypharmacy. Patients at high risk of suicide tended to have inadequate therapy and poor compliance, which should be assessed and treated adequately during hospitalization.Clinical trial registrationwww.ClinicalTrials.gov, Identifier: NCT01770704.

Dataset Information

PICU Length of Stay: Factors Associated With Bed Utilization and Development of a Benchmarking Model.

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PICU Length of Stay: Factors Associated With Bed Utilization and Development of a Benchmarking Model.

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